Whole exome sequencing enhances diagnosis of hereditary bronchiectasis
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Hereditary bronchiectasis refers to a subset of bronchiectasis related to genetic mutations, presenting with common clinical features. Historically, diagnosing this condition has been difficult due to the inaccessibility of diagnostic services coupled with a lack of awareness of the syndrome. We hypothesize that whole exome sequencing (WES) in patients with supporting clinical features, combined with non-genetic testing methods, will enhance the diagnosis of hereditary bronchiectasis. RESULTS: In total, 87 patients with clinical features suggestive of hereditary bronchiectasis, such as diffuse bronchiectasis (≥ 2 lobes) combined with early onset symptoms, recurrent otitis media, rhinosinusitis, infertility, organ laterality defects or a family history of bronchiectasis, were included in this study. Among them, 49.4% (43/87) were diagnosed with hereditary bronchiectasis, including 15 patients with cystic fibrosis, 27 patients with primary ciliary dyskinesia, and 1 patient with immunodeficiency-21. The combined use of WES and non-genetic testing methods significantly improved the diagnostic rate of hereditary bronchiectasis compared to non-genetic testing alone (47.1% vs. 25.3%, P = 0.005). Re-analysis of negative commercial genetic tests led to two additional diagnoses, though this increase was not statistically significant (47.1% vs. 49.4%, P = 0.879). CONCLUSIONS: We have described the supporting clinical features of patients with hereditary bronchiectasis. Clinicians should recommend WES for patients exhibiting these characteristics, in combination with accessible non-genetic testing methods, to maximize diagnostic accuracy. For patients with negative initial genetic test results, re-analysis of WES data may facilitate obtaining a new diagnosis.
Authors: Wangji Zhou, Yixuan Li, Haixia Zheng, Miao He, Miaoyan Zhang, Qiaoling Chen, Christopher Situ, Yaqi Wang, Ting Zhang, Keqi Chen, Jinrong Dai, Shuzhen Meng, Xueqi Liu, Aohua Wu, Yaping Liu, Kai-Feng Xu, Xinlun Tian, Xue Zhang
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,990
OpenAlex ID: W4408782897
